Framework for fault detection and localization in power distribution networks

Abstract

Systems and methods for detecting faults in a power distribution network are described. In an aspect, the systems and methods determine a probability that each node of the network is powered and a probability that each distribution line in the network is faulted. In another aspect, the systems and methods determine the probabilities by transmitting a signal over a power distribution network with an active sounding system. In an additional aspect, the systems and methods determine the probabilities by utilizing collected data coupled to the power distribution network.

The invention claimed is: 
     
       1. A system for detecting faults in a power distribution network, the power distribution network comprising a plurality of nodes connected by a plurality of transmission lines, the system comprising:
 one or more sensing devices coupled to the power distribution network, the sensing devices receiving stochastic data from the power distribution network representative of a power state of each of the plurality of nodes and whether each of the plurality of transmission lines is faulted; 
 a memory device coupled to the one or more sensing devices, the memory device comprising a data management module, the data management module storing the stochastic data received by the one or more sensing devices; 
 a processing device coupled to the memory device, the processing device comprising a processor configured to execute a probabilistic fault detection application, the probabilistic fault detection application including a query module, a fault probability estimation module, a reporting module, and a feedback module, wherein the probabilistic fault detection application comprises processor executable instructions stored on the memory device, wherein the instructions, when executed by the processor, configure the processor for:
 retrieving, via the query module, the received stochastic data from the memory device, wherein the retrieved stochastic data comprises the power state of each of the plurality of nodes and whether each of the plurality of transmission lines is faulted; 
 generating, via the fault probability estimation module based on the retrieved stochastic data, a first estimated probability that each node of the plurality of nodes of the power distribution network is powered, wherein said generating the first estimated probability comprises calculating a first marginal probability density function from a joint probability density function of the states of the plurality of nodes using a sum-product algorithm; 
 generating, via the fault probability estimation module based on the retrieved stochastic data, a second estimated probability that each transmission line of the plurality of transmission lines connecting the plurality of nodes is faulted, wherein said generating the second estimated probability comprises calculating a second marginal probability density function from a joint probability density function of the states of the plurality of transmission lines using the sum-product algorithm; 
 determining which of the plurality of nodes are powered and whether the distribution lines of the network connected thereto are faulted based on the first and second estimated probabilities; 
 generating, via the reporting module, a distribution map comprising the plurality of nodes and the plurality of transmission lines for display; 
 assigning, via the feedback module, a first visual characteristic to each node of the plurality of nodes on the distribution map to visually indicate the first estimated probability that the corresponding node is powered; and 
 assigning, via the feedback module, a second visual characteristic to each transmission line of the plurality of transmission lines on the distribution map to visually indicate the second estimated probability that the corresponding transmission line is faulted. 
 
 
     
     
       2. The system of  claim 1 , wherein determining the first estimated probability and the second estimated probability further comprises calculating messages to be sent between the nodes and transmission lines of a graph representative of the network. 
     
     
       3. The system of  claim 2 , wherein the messages comprise probability density functions. 
     
     
       4. The system of  claim 1 , wherein the data from the power distribution network comprises at least one of:
 very low frequency (VLF) sync detection data; 
 interactive voice response (IVR) data; 
 lineman observation data; 
 magnetic induction data; 
 supervisory control and data acquisition (SCADA) data; 
 infrared imagery data; 
 two-way automated communication system data; 
 radio frequency system data; and 
 cellular system data. 
 
     
     
       5. The system of  claim 1 , wherein the first visual characteristic and the second visual characteristic comprise a common visual characteristic. 
     
     
       6. A method for detecting faults in a power distribution network comprising:
 collecting stochastic data from a power distribution network comprising a plurality of nodes connected by a plurality of transmission lines, the stochastic data comprising a power state of each of the plurality of nodes and whether each of the plurality of transmission lines is faulted; 
 receiving the stochastic data at a processing device; 
 generating, by the processing device executing a fault probability estimation module and based on the received stochastic data, a first estimated probability that each node of the plurality of nodes of the power distribution network is powered, said generating the first estimated probability comprising calculating a first marginal probability density function from a joint probability density function of the states of the plurality of nodes via a sum-product algorithm; 
 generating, by the processing device executing the fault probability estimation module and based on the received stochastic data, a second estimated probability that each transmission line of plurality of transmission lines connecting the plurality of nodes is faulted, said generating the second estimated probability comprising calculating a second marginal probability density function from a joint probability density function of the states of the plurality of transmission lines via the sum-product algorithm; 
 determining which of the plurality of nodes are powered and whether the distribution lines of the network connected thereto are faulted based on the first and second estimated probabilities; 
 generating, by the processing device executing a reporting module, a distribution map comprising graphical representations of the plurality of nodes and the plurality of transmission lines for display via a display device; 
 assigning, by the processing device executing a feedback module, a first visual characteristic to the graphical representation of each node of the plurality of nodes to visually indicate the first estimated probability that the corresponding node is powered; and 
 assigning, by the processing device executing the feedback module, a second visual characteristic to the graphical representation of each transmission line of the plurality of transmission lines to visually indicate the second estimated probability that the corresponding transmission line is faulted. 
 
     
     
       7. The method of  claim 6 , wherein determining the first estimated probability and the second estimated probability further comprises calculating messages to be sent between the nodes and transmission lines of a graph representative of the network. 
     
     
       8. The method of  claim 7 , wherein the messages comprise probability density functions. 
     
     
       9. The method of  claim 6 , wherein the data from the power distribution network comprises at least one of:
 very low frequency sync detection data; 
 interactive voice response (IVR) data; 
 lineman observation data; 
 magnetic induction data; 
 supervisory control and data acquisition (SCADA) data; 
 infrared imagery data; 
 two-way automated communication system data; 
 radio frequency system data; and 
 cellular system data. 
 
     
     
       10. The method of  claim 6 , wherein the data are collected by one or more sensing devices that are observing the power distribution network and capable of relaying their data to the processing device. 
     
     
       11. The method of  claim 6 , wherein the first visual characteristic and the second visual characteristic comprise a common visual characteristic. 
     
     
       12. A method for detecting faults in a power distribution network, comprising:
 transmitting, by a concentrator device, a signal to a plurality of nodes in the power distribution network; 
 notifying a central processing station, by the concentrator device, of said transmitting; 
 receiving, by the plurality of nodes, the transmitted signal; 
 monitoring, by the central processing station for one or more nodes of the plurality of nodes, a detection status of the received signal; 
 generating, by the central processing station based on the detection status, a first estimated probability that each node of the plurality of nodes is powered, said generating the first estimated probability comprising calculating a first marginal probability density function from a joint probability density function of the detection status of the plurality of nodes via a sum-product algorithm; 
 generating, by the central processing station based on the detection status, a second estimated probability that each distribution line of a plurality of distribution lines connecting the plurality of nodes is faulted, said generating the second estimated probability comprising calculating a second marginal probability density function from a joint probability density function of the detection status of the plurality of nodes via the sum-product algorithm; and 
 determining which of the plurality of nodes are powered and whether the distribution lines of the network connected thereto are faulted based on the first and second estimated probabilities. 
 
     
     
       13. The method of  claim 12 , wherein the detection status comprises an attribute indicative of a detection of the transmitted signal by one or more nodes of the plurality of nodes. 
     
     
       14. The system of  claim 1 , wherein the instructions, when executed by the processing device, configure the probabilistic fault detection application for providing, via the feedback module when the generated first estimated probability for one or more nodes of the plurality of nodes is uncertain, feedback to the one or more sensing devices to collect data from the one or more nodes corresponding to the uncertain first estimated probability. 
     
     
       15. The system of  claim 1 , wherein the instructions, when executed by the processing device, configure the probabilistic fault detection application for providing, via the feedback module when the generated first estimated probability for one or more nodes of the plurality of nodes is uncertain, feedback to the one or more sensing devices to collect data from one or more nodes neighboring each of the one or more nodes corresponding to the uncertain first estimated probability. 
     
     
       16. The method of  claim 10 , further comprising providing, by the processing device executing the feedback module when the generated first estimated probability for one or more nodes of the plurality of nodes is uncertain, feedback to the one or more sensing devices to collect data from the one or more nodes corresponding to the uncertain first estimated probability. 
     
     
       17. The method of  claim 10 , further comprising providing, by the processing device executing the feedback module when the generated first estimated probability for one or more nodes of the plurality of nodes is uncertain, feedback to the one or more sensing devices to collect data from one or more nodes neighboring each of the one or more nodes corresponding to the uncertain first estimated probability.